ArticleJournal of medical Internet research2021
Understanding the Public Discussion About the Centers for Disease Control and Prevention During the COVID-19 Pandemic Using Twitter Data: Text Mining Analysis Study.
Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Article
- Effectiveness of Cognitive Behavioral Therapy (CBT) on Psychological Distress among Mothers of Children with Autism Spectrum Disorder: The Role of Problem-Solving Appraisal.Behavioral sciences (Basel, Switzerland) · 2024Article
- Comparison of Impressions of COVID-19 Vaccination and Influenza Vaccination in Japan by Analyzing Social Media Using Text Mining.Vaccines · 2023Article
- COVID-19, Genetics, and Risk: Content Analysis of Facebook Posts Early in the Coronavirus Pandemic.Health communication · 2023Article
- [Sentiments in the COVID-19 crisis communication of German authorities and independent experts on Twitter : A sentiment analysis for the first year of the pandemic].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2023Article
- Effects of Chinese provincial CDCs WeChat official account article features on user engagement during the COVID-19 pandemic.Journal of global health · 2023Article
- Article
- The Spread of COVID-19 Crisis Communication by German Public Authorities and Experts on Twitter: Quantitative Content Analysis.JMIR public health and surveillance · 2021Article
- Nursing Perspectives on the Impacts of COVID-19: Social Media Content Analysis.JMIR formative research · 2021Article
- A Large-Scale COVID-19 Twitter Chatter Dataset for Open Scientific Research-An International Collaboration.Epidemiologia (Basel, Switzerland) · 2021Article
- COVID-19 Vaccine-Related Discussion on Twitter: Topic Modeling and Sentiment Analysis.Journal of medical Internet research · 2021Article
- Making sense of COVID-19 over time in New Zealand: Assessing the public conversation using Twitter.PloS one · 2021Article
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Authors and funding
2 authors.
Funding
Abstract
backgroundThe Centers for Disease Control and Prevention (CDC) is a national public health protection agency in the United States. With the escalating impact of the COVID-19 pandemic on society in the United States and around the world, the CDC has become one of the focal points of public discussion.
objectiveThis study aims to identify the topics and their overarching themes emerging from the public COVID-19-related discussion about the CDC on Twitter and to further provide insight into public's concerns, focus of attention, perception of the CDC's current performance, and expectations from the CDC.
methodsTweets were downloaded from a large-scale COVID-19 Twitter chatter data set from March 11, 2020, when the World Health Organization declared COVID-19 a pandemic, to August 14, 2020. We used R (The R Foundation) to clean the tweets and retain tweets that contained any of five specific keywords-cdc, CDC, centers for disease control and prevention, CDCgov, and cdcgov-while eliminating all 91 tweets posted by the CDC itself. The final data set included in the analysis consisted of 290,764 unique tweets from 152,314 different users. We used R to perform the latent Dirichlet allocation algorithm for topic modeling.
resultsThe Twitter data generated 16 topics that the public linked to the CDC when they talked about COVID-19. Among the topics, the most discussed was COVID-19 death counts, accounting for 12.16% (n=35,347) of the total 290,764 tweets in the analysis, followed by general opinions about the credibility of the CDC and other authorities and the CDC's COVID-19 guidelines, with over 20,000 tweets for each. The 16 topics fell into four overarching themes: knowing the virus and the situation, policy and government actions, response guidelines, and general opinion about credibility.
conclusionsSocial media platforms, such as Twitter, provide valuable databases for public opinion. In a protracted pandemic, such as COVID-19, quickly and efficiently identifying the topics within the public discussion on Twitter would help public health agencies improve the next-round communication with the public.
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